Cereal Research Communications

, Volume 47, Issue 1, pp 134–144 | Cite as

Genetic Diversity among Tropical Provitamin A Maize Inbred Lines and Implications for a Biofortification Program

  • J. P. SserumagaEmail author
  • D. Makumbi
  • M. L. Warburton
  • S. O. Opiyo
  • G. Asea
  • A. Muwonge
  • C. L. Kasozi


Insights into the diversity and relationships among elite breeding materials are an important component in maize improvement programs. We genotyped 63 inbred lines bred for high levels of provitamin A using 137 single nucleotide polymorphism markers. A total of 272 alleles were detected with gene diversity of 0.36. Average genetic distance was 0.36 with 56% of the pairs of lines having between 0.30 and 0.40. Eighty-six percent of the pairs of lines showed relative kinship values <0.50, which indicated that the majority of these provitamin A inbred lines were unique. Relationship pattern and population structure analysis revealed presence of seven major groups with good agreement with Neighbour Joining clustering and somewhat correlated with pedigree and breeding origin. Utilization of this set of provitamin A lines in a new biofortification program will be aided by information from both molecular-based grouping and pedigree analysis. The results should guide breeders in selecting parents for hybrid formation and testing as a short-term objective, and parents with diverse alleles for new breeding starts as a long-term objective in a provitamin A breeding program.


maize inbred SNP provitamin 


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Genetic Diversity among Tropical Provitamin A Maize Inbred Lines and Implications for a Biofortification Program


  1. Adeyemo, O., Menkir, A., Melaku, G., Omidiji, O. 2011. Genetic diversity assessment and relationship among tropical yellow endosperm maize inbred lines using SSR markers. Maydica 56:1703.Google Scholar
  2. Adeyemo, O., Omidiji, O. 2014. SSR-based and carotenoid diversity assessment of tropical yellow endosperm maize inbred lines. Plant Genet. Resour.-C. 12:67–73.CrossRefGoogle Scholar
  3. Azmach, G., Melaku, G., Menkir, A., Spillane, C. 2013. Marker-trait association analysis of functional gene markers for provitamin A levels across diverse tropical yellow maize inbred lines. BMC Plant Biol. 13:227.CrossRefGoogle Scholar
  4. Badu-Apraku, B., Oyekunle, M., Fakorede, M.A.B., Vroh, I., O Akinwale, R., Aderounmu, M. 2013. Combining ability, heterotic patterns and genetic diversity of extra-early yellow inbreds under contrasting environments. Euphytica 192:413–433.CrossRefGoogle Scholar
  5. Bradbury, P., Zhang, Z., Kroon, D., Casstevens, T., Ramdoss, Y., Buckler, E. 2007. TASSEL: software for association mapping of complex traits in diverse samples. Bioinformatics 23:2633–2635.CrossRefGoogle Scholar
  6. Brunson, A., Quackenbush, F. 1962. Breeding corn with high provitamin A in the grain. Crop Sci. 2:344–347.CrossRefGoogle Scholar
  7. Cairns, J.E., Sonder, K., Zaidi, P.H., Verhulst, N., Mahuku, G., Babu, R., Nair, S.K., Das, B., Govaerts, B., Vinayan, M.T. 2012. Maize production in a changing climate: Impacts, adaptation, and mitigation strategies. Adv. Agron. 114:1–58.CrossRefGoogle Scholar
  8. Dao, A., Sanou, J., Mitchell, S.E., Gracen, V., Danquah, E.Y. 2014. Genetic diversity among INERA maize inbred lines with single nucleotide polymorphism (SNP) markers and their relationship with CIMMYT, IITA, and temperate lines. BMC Genetics 15:127.CrossRefGoogle Scholar
  9. Evanno, G., Regnaut, S., Goudet, J. 2005. Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Molecular Ecolology 14:2611–2620.CrossRefGoogle Scholar
  10. Farfan, I.D.B., De La Fuente, G.N., Murray, S.C., Isakeit, T., Huang, P.-C., Warburton, M., Williams, P., Windham, G.L., Kolomiets, M. 2015. Genome wide association study for drought, aflatoxin resistance, and important agronomic traits of maize hybrids in the sub-tropics. PLoS One 10, e0117737.CrossRefGoogle Scholar
  11. Fiedler, J.L., Afidra, R. 2010. Vitamin A fortification in Uganda: Comparing the feasibility, coverage, costs, and cost-effectiveness of fortifying vegetable oil and sugar. Food Nutr. Bull. 31:193–205.CrossRefGoogle Scholar
  12. Hardy, O., Vekemans, X. 2002. SPAGeDi: a versatile computer program to analyse spatial genetic structure at the individual or population levels. Mol. Ecol. Notes. 2:618–620.CrossRefGoogle Scholar
  13. Ligges, U., Mächler, M. 2002. Scatterplot3d – an R package for visualizing multivariate data. J. Stat. Softw. 8:1–20.Google Scholar
  14. Liu, K., Muse, S.V. 2005. PowerMarker: an integrated analysis environment for genetic marker analysis. Bioinformatics 21:2128–2129.CrossRefGoogle Scholar
  15. Liu, K., Goodman, M., Muse, S., Smith, J., Buckler, E., Doebley, J. 2003. Genetic structure and diversity among maize inbred lines as inferred from DNA microsatellites. Genetics 165:2117–2128.PubMedPubMedCentralGoogle Scholar
  16. Lu, Y., J. Yan, C., Guimarães, S., Taba, Z., Hao, S., Gao, S., Chen, J., Li, S., Zhang, B., Vivek, C., Magorokosho, S., Mugo, D., Makumbi, S., Parentoni, T., Shah, T., Rong, J., Crouch, Y. Xu. 2009. Molecular characterization of global maize breeding germplasm based on genome-wide single nucleotide polymorphisms. Theor. Appl. Genet. 120:93–115.CrossRefGoogle Scholar
  17. Melchinger, A., Lee, M., Lamkey, K., Hallauer, A., Woodman, W. 1990. Genetic diversity for restriction fragment length polymorphisms and heterosis for two diallel sets of maize inbreds. Theor. Appl. Genet. 80:488–496.CrossRefGoogle Scholar
  18. Menkir, A., Maziya-Dixon, B., Mengesha, W., Rocheford, T., Alamu, E.O. 2017. Accruing genetic gain in provitamin A enrichment from harnessing diverse maize germplasm. Euphytica. 213:105.CrossRefGoogle Scholar
  19. Menkir, A., Olowolafe, M.O., Ingelbrecht, I., Fawole, I., Badu-Apraku, B., Vroh, B.I. 2006. Assessment of testcross performance and genetic diversity of yellow endosperm maize lines derived from adapted × exotic backcrosses. Theor. Appl. Genet. 113:90–99.CrossRefGoogle Scholar
  20. Muthusamy, V., Hossain, F., Thirunavukkarasu, N., Choudhary, M., Saha, S., Bhat, J.S., Prasanna, B.M., Gupta, H.S. 2014. Development of β-carotene rich maize hybrids through marker-assisted introgression of β-carotene hydroxylase allele. PLoS One 9:e113583.CrossRefGoogle Scholar
  21. Olmos, S., Delucchi, C., Ravera, M., Negri, M., Mandolino, C., Eyhérabide, G. 2014. Genetic relatedness and population structure within the public Argentinean collection of maize inbred lines. Maydica, 59:16–31.Google Scholar
  22. Pixley, K., Palacios-Rojas, N., Babu, R., Mutale, R., Surles, R., Simpungwe, E. 2013. Biofortification of maize with provitamin A carotenoids. In: S.A. Tanumihardjo (ed.), Carotenoids and Human Health, (pp. 271–292). Springer Science + Business Media, New York, NY. CrossRefGoogle Scholar
  23. Pritchard, J., Stephens, M., Donnelly, P. (2000). Inference of population structure using multilocus genotype data. Genetics 155:945–959.PubMedPubMedCentralGoogle Scholar
  24. Pritchard, J., Stephens, M., Donnelly, P. 2000. Inference of population structure using multilocus genotype data. Genetics 155:945–959.PubMedPubMedCentralGoogle Scholar
  25. Rafalski, A. 2002. Applications of single nucleotide polymorphisms in crop genetics. Curr. Opin. Plant Biol. 5:94–100.CrossRefGoogle Scholar
  26. Reif, J., Melchinger, A., Xia, X., Warburton, M., Hoisington, D., Vasal, S. 2003. Genetic distance based on simple sequence repeats and heterosis in tropical maize populations. Crop Sci. 43:1275–1282.CrossRefGoogle Scholar
  27. Rogers, J.S. 1972. Measures of genetic similarity and genetic distance. In: Studies in Genetics VII, University of Texas Publication 7213, Austin, pp. 145–153.Google Scholar
  28. Semagn, K., Magorokosho, C., Vivek, B., Makumbi, D., Beyene, Y., Mugo, S., Prasanna, B., Warburton, M. 2012. Molecular characterization of diverse CIMMYT maize inbred lines from eastern and southern Africa using single nucleotide polymorphic markers. BMC Genomics 13:113.CrossRefGoogle Scholar
  29. Sserumaga, J.P., Makumbi, D., Hyeonso, J., Kiarie, N., James, W.M., George, N.C.W., Lee, S.-M., Godfrey, A., Hakbum, K. 2014. Molecular characterization of tropical maize inbred lines using microsatellite DNA markers. Maydica 59:267–274.Google Scholar
  30. Suwarno, W.B., Pixley, K.V., Palacios-Rojas, N., Kaeppler, S.M., Babu, R. 2014. Formation of heterotic groups and understanding genetic effects in a provitamin A biofortified maize breeding program. Crop Sci. 54:14–24.CrossRefGoogle Scholar
  31. Suwarno, W.B., Pixley, K.V., Palacios-Rojas, N., Kaeppler, S.M., Babu, R. 2015. Genome-wide association analysis reveals new targets for carotenoid biofortification in maize. Theor. Appl. Genet. 128:851–864.CrossRefGoogle Scholar
  32. Tamura, K., Peterson, D., Peterson, N., Stecher, G., Nei, M., Kumar, S. 2011. MEGA5: Molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods. Mol. Biol. Evol. 28:2731–2739.CrossRefGoogle Scholar
  33. Van Inghelandt, D., Melchinger, A., Lebreton, C., Stich, B. 2010. Population structure and genetic diversity in a commercial maize breeding program assessed with SSR and SNP markers. Theor. Appl. Genet. 120:1289–1299.CrossRefGoogle Scholar
  34. Warburton, M.L., Xia, X.C., Crossa, J., Franco, J., Melchinger, A.E., Frisch, M., Bohn, M., Hoisington, D.A. 2002. Genetic characterization of CIMMYT maize inbred lines and open pollinated populations using large scale fingerprinting methods. Crop Science 42:1832–1840.CrossRefGoogle Scholar
  35. Wen, W., Araus, J., Trushar, S., Cairns, J., Mahuku, G., Bänziger, M. 2011. Molecular characterization of a diverse maize inbred line collection and its potential utilization for stress tolerance improvement. Crop Sci. 51:2569–2581.CrossRefGoogle Scholar
  36. West, K.P. Jr. 2002. Extent of vitamin A deficiency among preschool children and women of reproductive age. J. Nutr. 132:2857S–2866S.CrossRefGoogle Scholar
  37. Wu, Y., San Vicente, F., Huang, K., Dhliwayo, T., Costich, D.E., Semagn, K., Sudha, N., Olsen, M., Prasanna, B.M., Zhang, X., Babu, R. 2016. Molecular characterization of CIMMYT maize inbred lines with genotyping-by-sequencing SNPs. Theor. Appl. Genet. 129:753–765.CrossRefGoogle Scholar
  38. Xia, X.C., Reif, J.C., Melchinger, A.E., Frisch, M., Hoisington, D.A., Beck, D., Pixley, K., Warburton, M.L. 2005. Genetic diversity among CIMMYT maize inbred lines investigated with SSR markers. II. Subtropical, tropical mid-altitude, and highland maize inbred lines and their relationships with elite U.S. and European maize. Crop Sci. 45:2573–2582.Google Scholar

Copyright information

© Akadémiai Kiadó, Budapest 2019

Authors and Affiliations

  • J. P. Sserumaga
    • 1
    Email author
  • D. Makumbi
    • 2
  • M. L. Warburton
    • 3
  • S. O. Opiyo
    • 4
  • G. Asea
    • 1
  • A. Muwonge
    • 1
  • C. L. Kasozi
    • 1
  1. 1.Cereals Program, National Agricultural Research OrganizationNational Crops Resources Research InstituteKampalaUganda
  2. 2.International Maize and Wheat Improvement Center (CIMMYT)NairobiKenya
  3. 3.USDA ARS Corn Host Plant Resistance Research UnitUSA
  4. 4.Molecular and Cellular Imaging CenterOhio State UniversityColumbusUSA

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